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focuses on the development of GPU-accelerated, high-fidelity thermal runaway simulation models for lithium-ion battery cells, modules, packs, and complete battery systems. Thermal runaway is a chain
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. Experience and expertise in human mobility simulation and prediction with agent-based modeling and deep learning techniques. Proficient in Python programming for geospatial data processing, modeling, and
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equivalent foreign degree, obtained within the last three years prior to the application deadline Experience with simulation frameworks, system-level performance evaluation, or machine learning, is highly
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complete according to the instructions in the ad. The application must include: CV including relevant professional experience and knowledge. Please include a list of courses you have taught previously. Copy
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professional experience and knowledge. (max 2 pages) Copy of diplomas and grades from your previous university studies. Translations into English or Swedish if the original documents have not been issued in any
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physically consistent predictions. You will contribute to models that link composition, processing, microstructure and properties, and support novel alloy and process design targeting key industrial challenges
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or an equivalent foreign degree, obtained within the last three years prior to the application deadline Experience of experimental synthesis or process work under explicit safety requirements
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of Applied Nuclear Physics at Uppsala University conducts research and education in applied nuclear physics and nuclear engineering. The research includes modelling and simulation of nuclear fuel behaviour in
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to industrial processes—yet remains difficult to harvest efficiently with existing technologies. HEAT-BRIDGE addresses this challenge by bringing together ionic thermoelectrics, electrochemistry, mixed ionic
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education are performed in the areas of Communications, Antennas and Optical Networks, Systems and Control, Signal processing and Biomedical engineering, and Electric Power Engineering. We work with